• International Journal of Human Ecology
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• v.5 no.1
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• pp.83-95
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• 2004

The purpose of the study was to examine the determinants of financial well-being of the baby boomers. With data on 1,789 households from the 1998 Survey of Consumer Finances, the study provided a profile of baby boomers using demands, resources, financial attitudes, and financial practices. The descriptive statistics showed that 18% of the baby boomers were financially well off showing that they met the guidelines for two financial ratios: liquidity and solvency ratio. The results of logistic analysis on the measures of financial well-being revealed that financial management practices played an important role in predicting boomer's financial well-being. This suggested a positive approach of financial education to the baby boomers to help them manage their current finance well as well as prepare for their retirement.

• Annual Conference of KIPS
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• 2015.10a
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• pp.832-834
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• 2015

최근 CCRA(Common Criteria Recognition Arrangement) 협정서 개정에 따라 공통평가기준인 CC(Common Criteria) 평가제도에 변화가 생기고 있다. 현재의 CC 평가제도가 가지는 한계를 보완하고자 PP(protection profile)를 대신하는 cPP(collaborative protection profile)가 개발되었는데, 기존의 폐쇄적으로 운영되던 PP 개발 프로세스와 달리 cPP 개발에는 CCRA 회원국의 여러 기관 및 기업이 적극적으로 개발에 참여할 수 있다. 따라서 현재 세계 각국에서 cPP 개발에 관한 논의가 활발히 진행되고 있으며 세분화된 연구도 요구되고 있다. 본 논문에서는 기존의 CC 평가제도가 가지는 한계를 살펴보고 이러한 한계를 극복하기 위한 cPP의 등장 및 개정되는 새로운 CC 평가제도의 운영을 분석한다.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.4
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• pp.9-20
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• 2018

Global rating agencies, such as Moody's and S&P, have assigned credit ratings to corporate bonds issued by Japanese firms since 1980s. Local Japanese rating agencies, such as R&I and JCR, have more market share than the global raters. We examine the yield spreads of 1,050 yen-denominated corporate bonds issued by financial firms in Japan from 1998 to 2014 and find no evidence that bonds rated by at least one global agency are associated with a significant reduction in the cost of debt as compared to those rated by only local rating agencies. Unlike non-financial firms, the reputation effect of global rating agencies does not exist for Japanese financial firms. We also observe that firms with less information asymmetry are more likely to acquire ratings from Moody's or S&P. Additionally, the firm's financial profile does not affect its choice to seek out ratings from global raters. Our findings are contradictory to those by Han, Pagano, and Shin (2012), who employ bonds issued by non-financial firms in Japan. Our conjecture is that the asymmetric nature of financial firms makes investors less likely to depend on a credit risk assessment by rating agencies in determining the yields of new bonds.

• Journal of the Korean Home Economics Association
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• v.46 no.1
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• pp.87-101
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• 2008

Using the 1999 National Survey of America's Families(NSAF), this study investigated the factors that affect child care expenses and examined financial and social support of single mother families in the U. S. In this study, 4,676 single mother families with children aged twelve and under are included for the analytical sample. About half of all single mother families with children under age 12 had some amount of child care expenses in 1999. Monthly child care expenses for those who had child care expenses was an average of $255 and it accounted for about 15 percent of their family earnings. The profile of financial and social support showed that about one-quarter of single mothers received financial support for child care, one-fifth received free child care by relatives and about 40 percent received child support payments from nonresident fathers. Tobit analysis results showed that the significant factors that affected child care expenses were mother's age, marital status, educational level, employment status, the numbers of children aged 0-5, family income, the receipt of public assistance and financial support for child care.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.733-736
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• 1996

Neural Network(NN) is known to be suitable for forecasting corporate bankruptcy because of discriminant capability. Bankruptcy prediciton on NN by now has mostly been studied based on financial indices at specific point of time. However, the financial profile of corporates fluctuates within a certain range with the elapse of time. Besides, we need a lot of data of different bankrupt types in order to apply NN for better bankruptcy prediciton. Therefore, we have decided to focus on textiles and clothing industries for bankruptcy prediction with limited data. One part of the collected data was used for training and calibration, and the other was used for verification. The model makes a learning with extended data from financial indices at specific point of time. The trained model has been tested and we could get a high hitting ratio relatively.

• Korean Management Science Review
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• v.14 no.2
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• pp.91-111
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• 1997

Neural Network(NN) is known to be suitable for forecasting corporate bankruptcy because of discriminant capability. Bandkruptcy prediction on NN by now has mostly been studied based on financial indices at specific point of time. However, the financial profile of corporates fluctuates within a certain range with the elapse of time. Besides, we need a lot of data of different bankrupt types in order to apply NN for better bankruptcy prediction. Therefore, We have decided to focus on textile and clothing industries for bankruptcy prediction with limited data. One part of the collected data was used for training and calibration, and the other was used for verification. The model makes a learning with extended data from financial indices at specific point of time. The trained model has been tested and we could get a high hitting ratio relatively.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.2
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• pp.91-91
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• 1989

Neural Network(NN) is known to be suitable for forecasting corporate bankruptcy because of discriminant capability. Bandkruptcy prediction on NN by now has mostly been studied based on financial indices at specific point of time. However, the financial profile of corporates fluctuates within a certain range with the elapse of time. Besides, we need a lot of data of different bankrupt types in order to apply NN for better bankruptcy prediction. Therefore, We have decided to focus on textile and clothing industries for bankruptcy prediction with limited data. One part of the collected data was used for training and calibration, and the other was used for verification. The model makes a learning with extended data from financial indices at specific point of time. The trained model has been tested and we could get a high hitting ratio relatively.

• The Journal of Asian Finance, Economics and Business
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• v.3 no.2
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• pp.21-31
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• 2016

Although the microfinance sector in Bangladesh is mainly driven by Non-Governmental-Organizations (NGOs), there are other types of Microfinance Institutions (MFIs) that also provide financial services to the poor. Despite the criticism of microfinance programs, the current poverty situation in Bangladesh still requires such programs for consistently battling poverty. Hence, the aim of this paper is to profile the microfinance sector based on their legal status and investigate any possible differences (if any) between them in various aspects. After a thorough investigation of the sector, it was found that around 33 million of the clients are being served by the mainstream MFIs (NGO and Grameen Bank) while another 10-15 million clients are served by other types of MFIs (financial cooperatives, credit unions, various ministries etc.), accounting for the one-third of the total population in Bangladesh. While the mainstream MFIs basically works with poor, other categories of MFIs are concerned with relatively wealthy clients. Looking into the financial performance and social intermediation of the MFIs, the NGO-MFIs performed better than other types of MFIs in the sector.

• Korean Journal of Social Welfare
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• v.57 no.3
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• pp.415-435
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• 2005

The purpose of this study was to investigate conceptual constructions which determined financial preparedness for retirement. This study was guided by two theoretical frameworks, planned behavior theory and hierarchical personality model. Based on two theories, the conceptual framework which aimed to explain financial preparedness for retirement were formulated. Data from 'The health and welfare profile of the elderly aged 65 and or older in Chung-choo city' was analyzed. The subjects consisted of 87 economically active elderly population. Structure equation model was employed for statistical analyses. The results of structure equation model revealed that the casual relationship between the level of perceived financial-planning knowledge and the level of financial preparedness for retirement was statistically significant. Also, the hypothesized structural model for financial preparedness for retirement had the good model fit. Implications for social work practice from this study were discussed.

• The KIPS Transactions:PartC
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• v.17C no.3
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• pp.223-232
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• 2010

Due to the advance of Internet, offline services are expanded into online services and a financial transaction company provides online services using internet baning systems. However, security problems of the internet banking systems are caused by a lack of security for developing the internet banking systems. Although the financial transaction company has applied existing internal and external standards, ISO 20022, ISO/IEC 27001, ISO/IEC 9789, ISO/IEC 9796, Common Criteria, etc., there are still vulnerabilities. Because the standards lack in a consideration of security requirements of the internet banking system. This paper is intended to explain existing standards and discusses a reason that the standards have not full assurance of security when the internet baning system is applied by single standard. Moreover we make an analysis of a security functions for the internet baning systems and then selects the security requirements. In this paper, we suggest a new protection profile of the internet baning systems using Common Criteria V.3.1 from the analysis mentioned above.